This research program will develop novel software and methods for monitoring distributed patterns of brain activation using real time functional magnetic resonance imaging (rtfMRI). This technology will be applied to the pain perception and regulation system with the ultimate goal of better understanding and controlling pain. These investigations further the NIH mission by advancing understanding of the functional importance of distributed brain mechanisms and their role in pain processing. This enabling technology will be useful for both the research community and potentially for monitoring and treating disease, including chronic pain. The work hypothesizes that it is possible to monitor distributed patterns of brain activation using rtfMRI;that subjects can be trained to control distributed patterns of activation;and that this training will impact cognitive processes. This application will produce the first commercially available software product designed for determining precisely when distributed patterns of brain activation occur in fMRI data, and the extent to which they are present. The software will compare the level of similarity at each moment, for example once per second, between the subject's brain activation pattern at that moment and a pre-defined 'reference'spatial pattern of brain activation, indicating when a given reference pattern is present, and to what extent. Previous fMRI methods have either focused on determining what the pattern of brain activation associated with a task is, by averaging over repeated trials, or measuring changes in activation in a single brain region of interest (ROI). fMRI benefits from its ability to measure activation from a very large number of brain regions simultaneously. The present method uses computation to harness this measurement and statistical power of combining the patterned activation data from hundreds or thousands of brain voxels at each time point. Previous work has established that human subjects can learn to control single regions of brain activation using rtfMRI, including regions involved with pain processing, with resultant changes in perceived pain. Successful preliminary pilot results have demonstrate that it is possible to monitor complex patterns of brain activation second-by-second in real time by measuring distributed fMRI patterns, that this information can be used to infer the cognitive/behavioral state of subjects in experimental paradigms, and that subjects can be successfully trained to control complex distributed patterns of brain activation. This project addresses two questions: 1) Is it possible to monitor distributed patterns of brain activation in real time? 2) Can subjects be trained to control/mimic distributed activation patterns? There are six specific aims:1) Generate a production quality version of rtfMRI pattern comparison software, 2) Write a software quality assurance module, 3) Test fMRI pattern comparison software and methods, 4) Demonstrate that subjects can learn to mimic reference activation patterns in the pain control system, 5) Compare different pattern comparison methods, 6) Measure changes in pain perception that result from rtfMRI-pattern training. The proposed research and development program will create a software application and methods for monitoring the pattern of activation in a person's brain second by second using functional magnetic resonance imaging while the person is inside an MRI scanner. Measuring the pattern of activation in a person's brain may allow physicians to monitor the impact on the brain of disease processes or treatments. This technology will provide a more powerful means than has previously been available to train patients to control their own brain activation through feedback in order to treat disease, and may become a method for treating chronic pain, one of the largest public health issues in the United States.